The cerebellum is emerging as an important brain region for the coordination of motor and cognitive behaviors. Developmental abnormalities of the cerebellum have been linked to autism, schizophrenia, and other disorders of human neural function. This grant proposes to acquire extensive new data sets for gene expression and cellular phenotypes over six epochs of cerebellar development in over 30 recombinant inbred (RI) strains of mice (BXD) and 15 single gene mutant mice. This data will be web-accessible via WebQTL. We will also develop and integrate web-based informatic and visualization tools for researchers to analyze our data sets, provide datasets of their own for analysis, and test hypotheses about the cellular and molecular development of the cerebellum. Four specific aims are proposed that will be supported by four core functions. In Aim 1, we will obtain the phenotypic data on the full spectrum of expressed genes and several quantifiable developmental processes in RI and mutant mice. This data will be integrated into a current database that houses an exceptional array of phenotypic data on the adult mouse brain, WebQTL. In Aim 2, we will use WebQTL, Bayesian method analysis, graph theoretical approaches to the identification of cliques in expression data, and latent semantic indexing of Medline references to mine data on the patterns, both in time and space, of expressed genes and cellular phenotypes. In Aim 3, we will use molecular (qRT-PCR), anatomical (in situ hybridization and immunocytochemistry) and experimental (siRNA) approaches to validate inferences about gene and phenotype relationships. Finally, in Aim 4, we will develop a web-accessible, 3D, high-end animation of the developing cerebellum that will be used for heuristic and experimental purposes. The data that is obtained and the tools that are constructed in this project will be fully open to the research community. This project is also designed to interface with several of the currently funded Human Brain Projects that look at the anatomy and cell biology of the adult mouse brain and cerebellum. The phenotypic data that is gathered will contribute to the growing understanding of the molecular and cellular bases of cerebellar development. Such information may help understand and treat disorders of cerebellar origin, such as the most common form of childhood brain cancer, the medullablastoma, which is believed to emanate from the developing granule cells of the cerebellum. In the long term, we hope to use the tools developed in this project to make predictions about the molecular pathways and cellular programs that are important to the well-being of the central nervous system